Shrimp is a very important source of protein which is patronized by almost half of the world's population, and hence a very important specie in aquaculture. There is the need for increase in shrimp production worldwide to meet consumer demands. However, shrimp production is hampered by high cost of commercial feeds. Increase in prices of fish oil and fish meal has led to calls for their substitute. This calls for substitute has resulted in researchers studying the nutritional requirement of shrimp. The rationale for this article is to review the literature available on recent studies toward the development of practical diets for shrimps focusing on the nutrients required by different species qualitatively as well as quantitatively. This review highlights on nutrient requirements with respect to growth and feed utilization. Digestibility of nutrients used in shrimp diets is also accounted for in this article

This study was conducted to investigate the effects of replacing dietary fish oil (FO) with palm oil (PO) in juvenile Nile tilapia, Oreochromis niloticus (9.34± 0.02g initial weight) with emphasis on growth performance, digestive enzyme activities as well as serum biochemical parameters. Also, lysozyme activity (LYZ), respiratory burst (RB), superoxide dismutase (SOD), catalase (CAT) and resistance to Streptococcus iniae were investigated. Fish were stocked in 15 rectangular fiber glass tanks (150× 60× 40 cm) at 40 fish per tank with water maintained at 210 litres. Fish were fed five isonitrogenous (33% crude protein) and isolipidic (10% lipid) diets with PO included at 0% (0% PO), 25% (25% PO), 50% (50%PO), 75% (75% PO) and 100% (100% PO) for 8 weeks. The findings demonstrated that growth, and feed utilization was not compromised when PO was used in place of FO either partially or totally. Except for protease activity which was not significantly altered, lipase and amylase activities were significantly altered when FO was replaced with PO. There were no significant differences among treatments for CAT, SOD and LYZ. Serum malondialdehyde (MDA) in fish fed 100% PO was significantly lower than all other groups whiles total antioxidant capacity (TAC) of fish fed 0% PO was significantly higher than all other groups. Fish fed 0% PO, 25% PO and 50% PO had glutathione reductase (GR) significantly higher than fish fed 75% PO and 100% PO. RB in fish fed 0% PO were significantly lower than fish fed 75% PO and 100% PO. Also, fish fed 0% PO had significantly lower total protein (TP) compared with groups fed 50% PO and 75% PO. Fish fed diets with PO had similar resistance ability to Streptococcus iniae as those fed diets with FO. However, the liver function was likely to be compromised due to the increase in aspartate amino transferase (AST) and alkaline phosphatas (ALP) along increasing PO inclusion levels. AST, total protein, triacylglycerol (TAG) and low-density lipoprotein cholesterol (LDL-C) were significantly higher (p<0.05) in groups fed higher levels of PO. This study therefore concludes that feeding tilapia fingerlings with diets containing PO affects antioxidant and innate immune parameters negatively due to the reduction in LYS, TAC, GR, MDA, CAT, SOD and GSHpx.

This paper reviews current knowledge on the role of smart tools and biosensors based on artificial intelligence in reducing seafood loss and wastage. This study shows that a variety of biosensors, categorised according to how they function, can be used to measure the quality of seafood. These include optical biosensors, enzyme-based biosensors, immunosensors, microbial biosensors, DNA-based biosensors, electrochemical biosensors, optical biosensors, tissue-based biosensors, and piezoelectric biosensors. Among these biosensors, optical biosensors, electrochemical biosensors, and mechanical biosensors are the most significant. Again, this study report that, for seafood traceability and management, a variety of smart solutions including blockchain technology, quick response (QR) codes, data analytics, digital twins, and radio frequency identification (RFID) tags can be utilised. Catch data, vessel tracking data, and data from the processing plant are some of the different data sources that can be utilised to trace seafood products. Artificial intelligence tools like neural networks, deep learning, machine learning, and others can be used to forecast and improve seafood quality. It is crucial to study the development of biosensors that can properly identify the earliest signs of seafood contamination or rotting.